What Is the Lifetime Risk of Physician-diagnosed Asthma in Ontario, Canada?
Bibliographic record
Abstract
RATIONALE: Asthma is the most common chronic respiratory disease in Canada. The estimates of risk of developing asthma may help researchers and health planners set research agendas, predict the burden of asthma on society, and target the at-risk population for asthma prevention, management, and control. OBJECTIVES: To estimate the lifetime risk of physician-diagnosed asthma. METHODS: All individuals aged 0-79 years living in Ontario, Canada on April 1, 1996 who had not been diagnosed with asthma were monitored for 11 years until March 31, 2007. They were censored when they were diagnosed with asthma, turned age 80 years, or died. The lifetime risk (from birth to age 79 yr) of physician-diagnosed asthma was calculated by a modified survival analysis technique. Results were stratified by sex, rurality, and neighborhood income. MEASUREMENTS AND MAIN RESULTS: Overall, the lifetime risk of physician-diagnosed asthma was 33.9%. Whereas the overall lifetime risk was higher in females (35.0 vs. 32.9%; P < 0.001), the cumulative risk was higher in males in early years. The lifetime risk was higher in individuals living in urban areas (34.5 vs. 30.1%; P < 0.001) or low-income neighborhoods (35.0% in the lowest income quintile vs. 32.2% in the highest; P < 0.001). CONCLUSIONS: Our estimated overall lifetime risk indicates that one of every three individuals in Ontario, Canada has physician-diagnosed asthma during one's lifetime.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".